Adaptive AI Tutors: Enhancing Student Engagement and Learning Outcomes through Personalized Feedback Loops
By: Dr. Daniel Brown, Prof. Jessica Green, Dr. Hiroshi Sato, Dr. Laura Martinez, Dr. Peter Wang
Published: 2026-01-01
View on arXiv →#cs.AI
Abstract
This research presents an innovative adaptive AI tutoring system designed to personalize the learning experience, significantly boosting student engagement and improving academic outcomes. The system provides real-time, tailored feedback and dynamically adjusts content based on individual student progress and learning styles, creating highly effective and individualized learning paths. It has the potential to revolutionize education by making personalized instruction scalable and accessible.